02524naa a2200241 a 450000100080000000500110000800800410001902200140006010000250007424501350009926000090023452017760024365000290201965000150204865000100206365000160207365300330208965300330212270000260215570000160218170000160219777300690221321636482024-04-16 2024 bl uuuu u00u1 u #d a1558-06441 aBUSSINGUER, J. DE F. aUnderstanding the Spatio-Temporal Behavior of Sentinel-1 SAR Vegetation Indices Over the Brazilian Savanna.h[electronic resource] c2024 aThe behavior of five synthetic aperture radar (SAR) vegetation indices, namely, the dual-pol radar vegetation index (DpRVI), radar vegetation index (RVI) dual-pol, polarimetric RVI (PRVI), dual-pol SAR vegetation index (DPSVI), and modified DPSVI (DPSVIm) was investigated. The indices were derived from Sentinel-1 data between 2017 and 2021 for three vegetation classes (Forest, Savanna, and Grassland) in the Brasilia National Park (BNP), Brazil. Temporal profile analysis showed that all indices followed a seasonal pattern directly linked with the rainfall regime in the study site. DpRVI and RVI were related to the rate of radar signal variation over the vegetation as a function of seasonality. PRVI, DPSVI, and DPSVIm were directly related to the classes’ biomass levels and its seasonal variations over time. Precipitation and seasonal vegetation structure changes were relevant drivers of the shift and spread of the indices’ spatial distributions over time. A phenomenon called the index equalization effect was observed mainly on rainy dates, shifting and spreading the classes’ distributions to the same value ranges and degrading its separability. From a populational perspective, all indices presented associative intersections between all vegetation classes, despite the influence of seasonality. From a local perspective, DpRVI and RVI had disjoint intersections; PRVI maintained the associative relationships; and DPSVI and DPSVIm provided almost a complete separation between Forest and Grassland in all seasons. In both perspectives, DPSVIm outperformed the other indices in separating the classes by presenting the less than 72.15% average overlaps between all populational distributions and the highest H0 rejection rates, above 97% over time. aSynthetic aperture radar aVegetation aRadar aVegetação aParque Nacional de Brasília aRadar de abertura sintética1 aBAPTISTA, G. M. DE M.1 aSANO, E. E.1 aLEAL, F. A. tIEEE Transactions on Geoscience and Remote Sensinggv. 62, 2024.